通用网络摄像机校准 [英] Generic web camera calibration

问题描述

我正在建立一个网站，该网站使用计算机视觉技术来完成出色的工作，并通过用户使用网络摄像头实时录制和上传视频。为此，我需要相机固有和失真参数。我正在尝试找出给定用户上传的视频来计算这些值的最佳方法。我们无法对用户可能上传的视频做出任何假设-但合理的假设是，视频中可能有人。我仍处于起步阶段，但是我很想知道其他人如何解决了这个问题。

I am building a website that does cool things using computer vision techniques, with videos live recorded and uploaded by users using their webcam. For this, I need camera intrinsic and distortion parameters. I am trying to figure out what would be the best way to compute these given the user uploaded videos. We can make no assumptions about what videos user might upload - but a reasonable assumption is that a human might be present in the video. I am still in the initial stages of this, but I am interested in knowing how others have solved this problem.

具体来说，以下是我将不胜感激的问题小组中有经验的人可能会评论：

To be specific, below are the questions that I would appreciate someone experienced in the group might comment upon:

• 可以使用哪些算法，库和技术来提取任何可用的常规网络摄像头的固有参数和失真参数在市场上？ [我说提取而不是校准，以包括内在参数只是方法调用而无需校准的情况。]


• 通常，您观察到多少差异市场上提供的网络摄像头的固有和失真参数？您是使用单个固有参数和失真参数对它们进行近似计算还是采用了什么方法？


• 在这些情况下，可以采用哪些相机自校准方法（如果有）？是否有可用的开源库或商业库可能会有帮助？


• 如果我们打算使用视频用户记录和上传来校准网络摄像头，则参数中的哪些假设（例如fx = = fy或没有失真参数对您来说有意义并听起来合理吗？


• 对所有摄像机合理地近似固有参数和失真参数是否有意义？验证特定网络摄像头的特定固有参数和失真参数的性能的合理方法是什么？


• 是否需要考虑其他任何问题？

• What algorithms, libraries and techniques are available to extract intrinsic and distortion parameters of any generic webcam available in the market? [I say "extract" and not "calibrate" to include cases where intrinsic parameters are just a method call away with no calibration necessary].
• In general, how much variance have you observed in the intrinsic and distortion parameters in the webcams available in the market? Did you approximate them with a single intrinsic and distortion parameters or what approach did you follow?
• What camera self-calibration methods, if any, could be employed in these scenarios? Are there any opensource or commercial libraries available which might be of some help?
• If we aim to calibrate the webcams using the videos user record and upload, what assumptions in the parameters [like fx==fy or no distortion params] makes sense and sounds reasonable to you?
• Would a reasonable approximation of intrinsic and distortion params for all the cameras make sense? What would be a reasonable approach to validate how good particular intrinsic and distortion parameters are for a specific webcam?
• Are there any other issues that need to be considered?

推荐答案

有时候我是一个坏消息的发源者：）所以我现在就这样做。

Sometimes I am the one who comes with the bad news :) So do I now.

对于您的几乎所有观点，明确的答案是否，无，不是，依此类推。仅针对最后一点，还有其他问题，答案不是不，而是一长串:)。

For almost all your points there the clear answer is No, None, Not, and so on. Only for the last point, with the other issues, the answer is not a no, but a long list :).

实际上，几乎不可能在没有棋盘和某些特定约束的情况下进行相机校准。

Actually, camera calibration without a chessboard and some specific constraints is almost impossible.

与在OpenCV的拼接模块中找不到假设校准。 Hovewer，这并不完美，并且不能用于随机视频。试试看。

The closest implementation to a no-assumptions calibration is found in the stitching module in OpenCV. Hovewer, it is not perfect, and it's not working on random videos. Give it a try.

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